Research On Dock Assignment And Truck Sequence In A Cross Docking System Considering The Unloading/Loading Sequences Of Cargos

With the development of logistics technology, the competition between companies is becoming more and more fierce. Every company is looking for a suitable strategy on supply chain management to make them more and more stronger. Cross-docking system is one of supply chain management strategys. Informatization results in the requirements of customs getting more diversified, the bathes of cargoes getting more less, the type of cargoes getting more and more, and the trucks’service times getting more and more. In this satuation, the service sequence of trucks is fixed, the fixed service sequence makes the cargoes which stay in inbound trucks and outbound trucks get a fixed unloading and loading sequence. So, in this paper, we study the sequence of trucks and the assignment of doors with a fixed unloading and loading sequence on cargoes, and our object is to minimize the makespan of cross-docking center.In this paper, we studied two scheduling model. One of them is the non-preemtion scheduling model. In this scheduling model, the loading and unloading process of trucks can not be interrupted. Once the trucks assigned to the door, they can not leave the door without the cargoes on them all been unloaded/loaded.The second scheduling model is the preemtion scheduling model. In this scheduling model, the unloading process of inbound trucks can be interruped, the loading process of outbound trucks is same to the non-preemtion scheduling model. But, in the preemtion scheduling model, the interrupting time is limited and the interrupt operation will build penalty time.In the first scheduling model, we built math model, and designed genetic algorithm, standard particle swarm optimization algorithm and improved particle swarm algorithm to solve this problem. Then, we divied the problem into different scale base the number of doors, the number of trucks and the number of cargoes’type in every single truck, and did many numerical experiments. At last, by comparing the experimental results of the three algorithms, it showed that the improved particle swarm optimization algorithm compared to the other two algorithms improved by more than 15% in solution accuracy.In the second scheduling model, we built math model too. And we knew that the improved particle swarm optimization performed better on truck scheduling problem than the other two algorithms did, so, in the part, we used improved particle swarm optimization to solve this problem. At the same, we also designed pso-tabu search to solve this problem. At last, we did many numerical experiments, it showed that the improved particle swarm optimization performed better than hybrid tabu search did solution accuracy, but performed wores in calculation time.In this paper, we studied the dock assignment and truck sequence in a cross docking system considering the unloading/loading sequences of cargos, and studied this problem in two kinds scheduling mode. We provided theoretical support for the actual scheduling...